Developing a hidden Markov model for assessing the health of preterm babies

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University of Canterbury

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Bachelor of Science with Honours

Premature babies, because of their underdeveloped biological systems, often display cardiorespiratory instabilities. Yet, at the same time, many paediatric illnesses also affect cardiorespiratory functions. For a certain baby, it can therefore be difficult to determine the cause of such instabilities, and this ramifies on treatment decisions. We look to develop a Hidden Markov Model for modelling the health of preterm babies, as this is useful for uncovering information on the hidden states of a system - in this case, the health of a premature baby. First, we provide a background for the study of Hidden Markov Models; meanwhile, we develop the variants of Hidden Markov Models that are most desirable for our application, and describe how inference can be made in each case.